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Automatic measurements of left ventricular volumes and ejection fraction by artificial intelligence: clinical validation in real time and large databases

Abstract

Aims Echocardiography is a cornerstone in cardiac imaging, and left ventricular (LV) ejection fraction (EF) is a key parameter for patient management. Recent advances in artificial intelligence (AI) have enabled fully automatic measurements of LV volumes and EF both during scanning and in stored recordings. The aim of this study was to evaluate the impact of implementing AI measurements on acquisition and processing time and test–retest reproducibility compared with standard clinical workflow, as well as to study the agreement with reference in large internal and external databases. Methods and results Fully automatic measurements of LV volumes and EF by a novel AI software were compared with manual measurements in the following clinical scenarios: (i) in real time use during scanning of 50 consecutive patients, (ii) in 40 subjects with repeated echocardiographic examinations and manual measurements by 4 readers, and (iii) in large internal and external research databases of 1881 and 849 subjects, respectively. Real-time AI measurements significantly reduced the total acquisition and processing time by 77% (median 5.3 min, P < 0.001) compared with standard clinical workflow. Test–retest reproducibility of AI measurements was superior in inter-observer scenarios and non-inferior in intra-observer scenarios. AI measurements showed good agreement with reference measurements both in real time and in large research databases. Conclusion The software reduced the time taken to perform and volumetrically analyse routine echocardiograms without a decrease in accuracy compared with experts.
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Category

Academic article

Language

English

Author(s)

  • Sindre Hellum Olaisen
  • Erik Smistad
  • Torvald Espeland
  • Jieyu Hu
  • David Francis Pierre Pasdeloup
  • Andreas Østvik
  • Svend Aakhus
  • Assami Rösner
  • Siri Malm
  • Michael Stylidis
  • Espen Holte
  • Bjørnar Leangen Grenne
  • Lasse Løvstakken
  • Håvard Dalen

Affiliation

  • SINTEF Digital / Health Research
  • UiT The Arctic University of Norway
  • University Hospital of North Norway
  • Nord Trondelag Hospital Trust
  • St. Olavs Hospital, Trondheim University Hospital
  • Norwegian University of Science and Technology

Year

2023

Published in

European Heart Journal-Cardiovascular Imaging

ISSN

2047-2404

Volume

25

Issue

3

Page(s)

383 - 395

View this publication at Norwegian Research Information Repository